AI Engineer

About Revley

Autonomous commerce starts here.

A merchant should be able to describe a store and have it exist — landing page, product pages, cart, checkout — then have the money layer underneath it run without a team watching it. Routing, tokenization, subscriptions, disputes. Agents do the work. The operator signs off on anything that moves money.

We start at the foundation, payments and tokenization, and build up: checkout, subscriptions, multi-processor routing, dispute prevention, and the agents that operate all of it. Not a collection of integrations. One system.

The Role

AgentMercer runs in production today. It reads a merchant’s operational state — orders, disputes, logistics, support volume, payment risk — decides what needs to happen, and acts across the stack. Work that took a team hours takes it seconds.

You will own that reasoning layer. This is not prompt tuning on top of someone else’s product. You are designing how an agent decides, what context it earns access to, where it must stop and ask, and how we prove after the fact that it behaved. The hard problems here are trust and consequence, not model selection.

Responsibilities

• Design and ship agent workflows that read live commerce state and take real action across checkout, payments, disputes, and support
• Build the tool-use layer — typed, permissioned actions with hard limits on anything that moves money
• Own the approval boundary: which decisions an agent executes alone, which require an operator signature, and how that line is enforced in code
• Build retrieval and context assembly over orders, subscriptions, processor events, and support history
• Define evaluation harnesses and regression suites so agent behavior is measurable, not anecdotal
• Instrument every agent decision for audit — inputs, reasoning, action taken, outcome
• Work directly with the founders on which parts of a merchant’s operation should be automated next

Required Qualifications

• Four or more years of professional software engineering experience, with production systems you can point to
• Strong backend engineering in TypeScript or Python, and comfort designing APIs and data models
• Hands-on experience shipping LLM-backed features to real users — tool calling, structured output, retrieval
• Sound judgment about failure modes: hallucination, prompt injection, silent degradation, and how to contain each
• Experience building evaluation and monitoring for non-deterministic systems
• Ability to operate independently in an early-stage environment and own a domain end to end

Preferred Qualifications

• Experience with agent frameworks or multi-step orchestration in production
• Background in fintech, payments, or another domain where an incorrect action has financial consequence
• Experience with human-in-the-loop review systems or approval workflows
• Familiarity with the Claude API and its tool-use patterns

Our Stack